Retrieval Augmented Generation (RAG) for Enhanced Context 🧠

Empower your mates with external knowledge! This feature introduces RAG (Retrieval Augmented Generation) capabilities, allowing mates to access and utilize information from your organization's document repositories.

• Phase 1: Integrated Document Uploads: Upload documents directly to allmates.ai for RAG. This phase includes optimized token usage via vector databases and embeddings, supporting numerous documents efficiently. 📄

• Phase 2: External Connectors: Connect to external data sources like Microsoft SharePoint, Google Workspace Drive, Confluence, Google Cloud Storage, and AWS. This expands the scope of knowledge accessible to your mates. 🔗

• Phase 3: Custom RAG Integration (Future): Connect to your own custom RAG system, providing maximum flexibility and control. ⚙️

This phased approach to RAG integration provides enhanced context for your mates, enabling more accurate and insightful responses. 👍